Quality evaluation method of electricity statistical index data

Abstract

The invention relates to a quality evaluation method of electricity statistical index data. The method comprises the following steps: obtaining to-be-evaluated electricity statistical index data according to the requirement of an actual evaluation purpose; choosing corresponding data quality evaluation indexes; making data quality evaluation rules corresponding to the data quality evaluation indexes; calculating the weight Wi of a quality evaluation index Ii, and setting an expected value Ei; performing detection and analysis on quality evaluation indexes of the statistical index data, and calculating the percentage Si of data that meets the quality evaluation index Ii; according to the weight Wi, the percentage Si and the set expected value Ei, respectively calculating the comprehensive evaluation value SA, the overall expected value SE and the relative difference SR of the statistical index data, and performing evaluation on the overall quality of the statistical index data according to defined evaluation grades; and processing evaluated unqualified statistical index data. The method provided by the invention can be applied to quality evaluation of electricity statistical index data in the power industry.

Description

technical field [0001] The invention relates to a data quality assessment method, in particular to a quality assessment method for power statistical index data applicable to the electric power industry. Background technique [0002] In recent years, with the rapid development of the power industry, various departments of the power company have accumulated more and more complex data, and at the same time, the demand for power statistical information is also increasing and the requirements are getting higher and higher. Statistical information plays an increasingly important role in corporate decision-making, business management and social responsibility. However, due to the artificial and non-artificial disturbances of the data acquisition system of the electric power company, the data quality of each data source will be uneven, coupled with some problems in the database itself, resulting in data loss and errors during data integration, resulting in overall data loss. If the...

AI Technical Summary

Problems solved by technology

However, due to the artificial and non-artificial disturbances of the data acquisition system of the electric power company, the data quality of each data source will be uneven, coupled with some problems in the database itself, resulting in data loss and errors during data integration, resulting in overall data loss. The quality is not high, which will affect the company's decision-making planning and development, so the quality assessment of statistical data will become a necessary link in the company's development process

[0003] In the existing technology, there is already a relatively complete power statistical index data system, but there are few quality assessment methods for the rationality, standardization and authenticity of the data in the statistical index data system, and the data quality assessment is often only scattered. Aiming at the more important indicators of data quality statistical indicators, such as consistency, uniqueness, completeness, etc., no systematic data quality evaluation method has yet been formed

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